Continuous Glucose Monitoring: What It Means for the Definition of Diabetes

I recently published a Commentary on CNBC about the future of glucose tracking using continuous glucose monitors.  Here is the link –  – and here is the Twitter thread that I wrote with further thoughts.

In my editorial on use, I cite this fantastic article on ‘glucotypes’ from geneticists & endocrinologists (). One of my favorite papers from 2018. I want to explain a bit more why I think this paper is so important.

First, here is the editorial in – on where I see use going in next few years in management of diabetes and increasingly in use for people not diagnosed with diabetes.

How we define ‘diabetes’ and make a diagnosis has changed dramatically over the decades. See a short presentation I gave on this in 2012 here – . We’ve progressed from urine testing to OGTT to fasting glucose to A1c.

The paper from Hall et al demonstrates that our current diagnostic tests are probably insufficient. They’re missing lots of people, now labeled as ‘normal,’ who shows actually have dysregulated insulin responses to glucose consumption.

Do these people have diabetes? Prediabetes? These categories were historically defined based on what we know about A1c correlating to risk of microvascular complications (ie retinopathy). That is, it is ‘worth’ diagnosing someone with diabetes if A1c correlates w increased risk.

Really, what we mean is, would the benefits of treatment for diabetes outweigh the harms of treatment for a person with a certain degree of risk based on their A1c?

But… A1c is just an average, fraught with issues. What really matters is, is a person metabolically healthy and are they at increased risk for heart disease or microvascular complications down the road? So, there is a long road ahead for future research here.

How do we categorize ppl based on insulin-glucose response seen with ? Are people with abnormal ‘glucotypes’ at higher risk for heart disease & microvascular complications? What are long-term outcomes? Will they change behavior & improve outcomes when faced w CGM data?

So, to summarize: Not only is a necessary tool for all with , & massively valuable for most with type 2 diabetes, but I believe its use will help us redefine what we think of as , how we define a continuum of risk and categorize individual physiologic responses.

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Diabetes Technology in 2018

Linking here to two resources I published recently:

First, my presentation at the April 2018 UCSF Diabetes CME course.  Those slides on a 2018 Update in Diabetes Technology are here:

Second, I wrote “A Clinician’s Guide to the Latest Diabetes Devices” for Medscape recently.  Here is the first section of that blog post:

This has been a huge year for technological advances in diabetes management. We are on a rapidly advancing path with continuous glucose monitoring (CGM) technology and finally approaching the holy grail of fully automated, closed-loop insulin delivery. Within a few years, patients with type 1 diabetes may never need to do another fingerstick or have another A1c test. For many clinicians, recent developments may seem to present an array of head-spinning options. Here, I’ll try to cut through the noise and focus on technologies that have the biggest implications for clinical practice and our patients.

CGM Data Directly to Your Smartphone

CGM technology has been advancing rapidly in accuracy, number of options, and ease of use, and the problem of inaccurate, painful, alarming, needy, and annoying CGMs feels long in the past. It is hard to believe that it was as recently as December 2016 that the US Food and Drug Administration (FDA) first decided that a CGM (the Dexcom G5®) was accurate enough to no longer require supplemental fingersticks for insulin dosing decisions.

In 2018, Dexcom released the G6 CGM, which is slimmer (and less likely to snag on clothing); requires no fingerstick calibration; and is the first to have the FDA indication of “interoperable,” meaning that it can “plug and play” in the future with other interoperable devices.

Medicare finally started covering CGMs in 2017, and in June 2018 agreed to stop blocking the ability of the Dexcom G5 (which is reimbursed by the Centers for Medicare & Medicaid Services) to transmit data directly to a smartphone, something most users of the G5 had already benefited from for a few years. This was a big deal, as I believe that the ability to view CGM data directly on a smartphone may be the technology advance that has most positively affected my patients with diabetes.

In the past year, billing codes for CGM improved to enable providers to be reimbursed for analysis and interpretation of CGM data. This brings diabetes management one step closer to population health, where a provider can review CGM data without an office visit; correspond with the patient over the telephone, by email, or by text; and be reimbursed for that work. I plan to try this out in my practice during the next few months, blocking off time every 1-2 weeks to review CGM data in web software and communicate recommendations to patients via our electronic health records portal or telephone, with no scheduled visit required.

Immediate Feedback, No Fingersticks Required

Of everything that has come out recently, Abbott’s FreeStyle® Libre Flash CGM has had the greatest impact on my practice. The Libre is a disk-shaped device worn on the back of the arm (see any recent photo of British prime minister Theresa May). My patients have been consistent in their appraisal that the Libre is relatively or even entirely painless to insert, nonintrusive on the arm, and stays on during activity or contact with water. Most important, it entirely changes their approach to diabetes management.

For more, please continue on to Medscape (free Medscape log-in required)

 

Smart Insulin Pens are here… finally.

The first “smart” insulin pen has finally hit the market. This is a big moment for diabetes care, as the digital toolbox expands. (I wrote a post in 2013 about this topic, asking for someone to make a smart insulin pen)

From the perspective of a person with diabetes, this has the potential to solve many daily challenges. First, did I remember to take my insulin dose? Or, did I recently take a dose and forget that I did, leaving me at risk for hypoglycemia if I inject now? Another key  question for a PWD is, how much “insulin on board” do I have (that is, how much of my recently injected insulin is still affecting me)? Of course, another key element is the ability to track and capture insulin doses and not have to write them down in a logbook for your doctor!

From the provider perspective, we gain a huge amount of data to help us help our patients make decisions and learn from their experiences. For years, if we wanted to review a glucose and insulin time series, we either needed a patient to write down numbers in a logbook or to put someone on an insulin pump. More recently, manually entering data into an app became an option. The “smart” insulin pen finally means that glucose and insulin data can relatively easily (and passively) be captured into one place. This can help guide care in real-time as well as for retrospective review and analysis.

For the many people with type 1 diabetes who do not want an insulin pump, and for the people with type 2 diabetes for whom a pump is not covered or necessary, these smart insulin pens are likely to offer real benefits.

The next ask?

An automated way to capture food intake!

 

Other sources:

DiabetesMine DData 2017 has some slideshows on smart insulin pens

 

A Lesson In Clinical Decision Support: We Cannot Defeat Human Nature

      Our UCSF Clinical Informatics group met a few months ago with several representatives from a major Health IT vendor. The vendor, we’ll call them RxLabs, is a provider of pharmaceutical related knowledge in many domains, including decision support tools for the EHR. Our conversation centered around how to better customize medication alerts. We talked about the popular topic of “alert fatigue,” and how to improve EHR decision support tools to improve their impact, rather than just being white noise annoying clinicians.
      The vendor was walking us through a slide-deck about their hypotheses and data about EHR medication alerts and we were having a vibrant discussion about how to improve provider adherence with decision support. We saw slide after slide about how to make pop-ups smarter and about trying to get more buy-in from providers with paying attention to alerts. After all, why would a provider trying to take care of her patient ignore an alert that is trying to help provide an important message? It must be sloppiness or laziness on the part of providers!
      Ten minutes in to this conversation about drug alerts, up pops the following:
Windows 7 Display Alert
      I’ll give you a second to guess what happened next.
      Without a moment’s hesitation or thought, the presenter clicked the little X in the upper right corner. Our conversation went on. More slides. More data about medication alerts in the EHR. Ten minutes later, guess what happened?
      Up came the same pop-up Windows alert. The presenter again, hastily, without paying attention, and perhaps giving a small huff of displeasure, clicked the little X in the upper right corner. More slides, ten more minutes, same thing. You get the idea.
      This happened three times, with each passing pop-up, the presenter becoming slightly more annoyed. The fourth time the pop-up appeared, my colleague Russ Cucina, the Associate CMIO at UCSF, paused the presenter to have us all read the pop-up alert message. We took ten seconds together to learn that selecting any of the three choices rather than clicking the “x” would have satisfied the alert and kept it from coming back.
      The room broke out into laughter. We all understood our own hypocrisy. We cannot defeat human nature.

Feedback Loops and Teachable Moments: The Future Diabetes Care Paradigm

The current paradigm of office visits every three months for PWDs (people with diabetes) is not the right model (nor is it for other similar chronic conditions).  The management of diabetes requires a patient to make dozens of daily self-management decisions.  “How much insulin should I give for this slice of pizza?  Do I need to eat a snack to prevent my blood sugar from going low before I go for a jog?”  Diabetes related questions and issues do not occur on an every-three month basis in synch with this current model for office visits.  They are predictably unpredictable.  Accordingly, to best serve our patients, our system must be flexible and nimble.

In the current model, I see a PWD in my office and let’s say, for example, that we decide together to make a change to his insulin to carbohydrate dosing ratio.  He then leaves my office and we wait three months to reconvene and see if that dosing plan change is working or not.  It’s not that it takes three months to decide.  We could probably know within a week or two if the change is working.  It’s just that healthcare isn’t set up that way.  Our entire world now, in every industry and facet of life, is about data, analytics, and metrics.  Other industries have learned that rapid feedback loops are effective.  Adjusting a PWD’s insulin to carbohydrate dosing ratio should be no different.  By the time he comes back to my office three months later, the opportunity for learning may already have been lost.  Neither one of us has gotten timely and relevant feedback about our decisions.  We may have lost the opportunity for a teachable moment.  Healthcare needs to develop a new model where these feedback loops are much tighter and much faster, actually capitalizing on opportunities for teachable moments.  (Sidebar: One doctor who realized this years ago was Dr. Jordan Shlain, who founded HealthLoop)  Research studies show that PWDs are more successful and confident with managing their diabetes when they feel like they have the backup and support of their clinical providers looking over their shoulders to make sure things are going ok.  If we were to design the system from scratch to accomplish these goals, we probably would not have built it to rest on the concept of office visits every three months.

So, what should be the future model of a Diabetes and Endocrinology clinical practice?  Here’s what I imagine my practice looking like in the (hopefully near) future.  Instead of having 16 office visit slots per day of 30 minutes each, I imagine myself seeing 5 patients a day for 45-60 minutes each, allowing us to take our time working together in person and truly addressing the needs and goals of the patient.  These longer visits are essential for a patient new to my practice, a patient with a complicated or unknown diagnosis, a patient with complications or a major change in their disease state, or for discussing major changes in therapeutic course or strategy.  The rest of my day will be spent using a dashboard to do remote population management, looking for trouble spots among my patient population and focusing in on those, and doing telemedicine, connecting with patients through video-chats to make more minor adjustments and to do brief “check ins.”  Ten minutes spent with a patient at the point where there is a teachable moment like a low blood sugar from walking the dog might be more effective than a standard 30 minute office visit every three months.  We’ll have to test this hypothesis, of course, but we must try it.

This is why I’m brimming with so much enthusiasm and excitement about working with the non-profit, Tidepool, who is building an open data platform and a new generation of software applications for the management of type 1 diabetes.  Tidepool will provide us with the technology infrastructure to reach this vision of more frequent feedback loops and teachable moments.  I’m also very excited about the work that my UCSF colleagues, Drs. Ralph Gonzales and Nat Gleason, are doing to pilot the use of telephone visits and e-visits with patients in place of office visits.  Their work is paving the way toward demonstrating efficacy of e-visits, helping to achieve payer reimbursement so that such a model can take root.

The Future of Diabetes Management: Social Networking and New Technologies

I gave a talk yesterday to a great crowd at the annual UCSF CME conference, Diabetes Update.  The slides from my presentation, “The Future of Diabetes Management: Social Networking and New Technologies,” can be viewed on Slideshare.

The Surgeon’s Viewpoint: Swedish Obese Subjects Study and Bariatric Surgery

The Swedish Obese Subjects study is a fabulous example of how very-useful practical knowledge can come out of a well-conducted cohort study.  Not everything has to be a prospective randomized controlled trial!   This study has produced a number of landmark papers which provide convincing evidence that:

1.       Bariatric surgery offers survival benefit over the long term for the morbidly obese, despite the up-front mortality risk from the surgery itself.

2.       Bariatric surgery reduces cardiovascular and cancer deaths

3.       Bariatric surgery is durable: most patients do not regain the weight back

4.       Not all bariatric procedures are the same.  Some work better than others.

5.       Diets, behavioral modification, and “professional” weight loss coaching doesn’t really work for the morbidly obese in the long haul.

6.       And now….bariatric surgery prevents onset of diabetes!

The strength of the Swedish Obese Subjects trial is in the follow-up.  Since Sweden has a nationalized health care system, follow-up was completed on >95% of the initial cohort.  Such a trial could never be conducted in the United States….our people change jobs, towns, or insurances just way too often!

And there is just one more thing you should know about the Swedish Obese Subjects trial: the vast majority of the surgery cohort underwent vertical banded gastroplasty (VBG).  What’s that, you ask?  It was a first-generation bariatric operation that has been abandoned worldwide in favor of better (i.e. more effective) operations, such as gastric bypass and sleeve gastrectomy.  So if this trial were repeated in 2012, we would expect even better results in the surgical arm with fewer complications.

So where does that leave us?  For any patient with BMI > 40 (or BMI >35 with metabolic disease), you should really get them thinking about surgery as an option.  It’s not just about weight, and certainly has nothing to do with cosmetic appearance.  It’s about getting serious about treating metabolic disease: diabetes, hypertension, sleep apnea, hypercholesterolemia, PCOS, and others.  It’s about making sure that those diseases never develop in the first place.  It’s about reducing overall cancer risk, stroke risk, and heart attack risk.  And it’s about improving overall quality and quantity of life.

So why, then, with such powerful clinical evidence, do less than 1% of adults who would benefit from bariatric surgery actually get it?  That, my friend, is complicated, and probably worth another blog in its own right!

Jonathan Carter, MD